Introduction: Due to the large amount of scientific evidence on the subject and the limitations and incongruities in previous reviews, the primary aim of this umbrella review is to gather all the information regarding the importance of vitamin D levels in the osseointegration of dental implants. Methods: The literature search was performed in PubMed, Web of Science, CINAHL Plus, Cochrane Library, and Academic Search Complete throughout the search expression [“vitamin D” AND (“dental implant” OR “dental implants”)]. Results: The initial search yielded 351 results, but at the end of the process, only five systematic reviews were selected. Conclusions: Vitamin D seems to have a positive effect on the osseointegration of dental implants and on the reduction of dental implant failures; however, it is recommended that future studies take into account the limitations mentioned in this study in order to increase the validity and quality of scientific evidence on the subject.

Introduction It is essential to understand, on a large geographical scale, the dimension of the COVID–19 pandemic by identifying the most affected countries, knowing that all the world is suffering an unusual disruption regarding several health impacts, but also heavy economic, financial and social effects. A key role is reserved to Data Science to understand the present and to deepen a prospective analysis at COVID–19 day after. Objective The main objective of the present study is to describe the COVID–19 prevalence in EU and five other OECD countries using five epidemiological variables. Secondly their association with non–pharmaceutical measures taken in some countries to control and attenuate the evolution of the epidemic was analyzed. Methods The COVID–19 study covers twenty–six EU countries and additionally Switzerland, Norway, Turkey, Israel and United Kingdom. Five epidemiologic variables were analyzed by 100.000 inhabitants at the beginning of May 2020: total number of cases, total number of deaths, total number of active cases, total number of critical or serious cases and total number of tests. Also, eight non–pharmaceutical measures were selected for association purposes. A multivariate statistical exploratory approach with principal components, hierarchical and non–hierarchical (k–means) cluster analyses was applied. Results A COVID–19 prevalence typology of four country clusters was identified regarding EU countries and five OECD countries on early May. In the two clusters, with a total of ten countries where the pandemic seemed to evolve more seriously, different patterns regarding the number of tests are observed. Two other clusters, with 12 and 9 countries, show an intermediate or low prevalence but differences in testing patterns. For EU countries of both clusters more affected, COVID–19 containment strategies were studied considering three modalities of implementation timing for eight non–pharmaceutical measures. The three different behaviors mirrored the clusters findings. Countries previously classified into cluster 1 appear together again, as do countries belonging to cluster 2. In spite of a common behavior for some measures, generally countries of cluster 2 implemented other interventions later in time. Sweden is a “special case”, taking just a few of these measures, most of them later than other countries.

Introduction: About a year and a half after the declaration of the COVID-19 pandemic, almost the entire planet has been affected by SARS-CoV-2 coronavirus and its variants, with serious public health consequences and other repercussions not yet thoroughly evaluated or foreseen in terms of economic, financial and social disruption throughout communities. Therefore, it is of utmost importance to understand the geography of the evolution of successive pandemic waves. Particularly in European countries, where, in recent decades, more advanced models for cohesion and competitiveness of a whole with more than 400 million inhabitants have been achieved, with ambitious challenges for horizon 2030 regarding this vast territory’s economic, social, and environmental sustainability. Objective: The main objective of this research is to describe the multivariate trajectories of COVID-19 incidence, mortality, hospital admissions, ICU admissions and testing, over three successive waves, covering all European Union (EU) countries with more than two million inhabitants, over 14-days periods before May 4 2020, until February 22 2021. Methods: This research includes 22 European countries representing about 98.8% of the EU population, described by six epidemiological variables over 43 time periods from the ECDC database: the 14-day notification rate Biometrics & Biostatistics International Journal Research Article Open Access of new cases reported for 100,000 inhabitants; the 14-day notification rate of reported deaths per one million inhabitants; the mean and the rate for 100,000 population of hospital occupancy and ICU occupancy; the testing rate per 100,000 population; and the 14-days percentage of test positivity. An exploratory data analysis of each epidemiological variable identified a typology of countries profiles evolution. Multivariate exploratory statistical methods, namely a 3-way data analysis (double principal components and rank principal components analyses), were applied with software R version 4.1.0. Results: The multivariate evolution profile of the COVID-19 pandemic in the EU over the studied period highlighted 3 phases: the first phase over 24 time periods, with a relatively low COVID-19 incidence, hitting only part of EU countries; a second phase at the beginning of the second wave, when COVID-19 spread to most countries, with a higher impact on national health systems; lastly, a third phase coincident with the peak of the second wave and the onset of the third wave, a particularly reactive phase from the public authorities, with intensified testing of the population. These results are clear from the principal component analysis of the centres of gravity of the 43 time periods (interstructure). The multivariate statistical analysis of the global dataset of all countries over the 43 time periods additionally provides the main factorial representation of the trajectories of COVID-19 for each country in direct comparison with the global average ranked values reached by the six epidemiological variables over the whole period under study (intrastructure). These trajectories make it possible to identify different country profiles throughout the successive pandemic waves and counter-cyclical behaviours, partly explained by the insufficient harmonisation of public policies to tackle the pandemic within the EU

Introduction: The pandemic generated by COVID–19 completely changed people's daily lives, their relationship with family and friends, unexpectedly disrupted their working conditions and enhanced the need for an enduring resilience to face yet a second wave of the disease. It is crucial to keep continuously updating our knowledge about COVID–19 prevalence and incidence evolutions over large connected territories, where the disease is striking in alarming proportions. Objective: The main objective of this research is to identify and describe COVID–19 prevalence, incidence and mortality profiles in EU and EEE/EFTA countries, seven months after the start of the pandemic in Europe, and more recent tendencies, probably associated to the beginning of a second wave. Methods: This COVID–19 study covers thirty–one European countries. Six epidemiological variables where analyzed per 100 000 inhabitants on October 25 2020, two of them evaluated over the seven previous days. A multivariate statistical exploratory analysis based on rank principal components and cluster analysis was applied. Results: A COVID–19 prevalence typology of six country clusters was identified regarding 31 countries (EU, UK and three EEE/EFTA countries). The five epidemiological variables and number of tests revealed a wider dispersion with outlier observations. The rank transformation of data and their multivariate statistical analysis allowed us to construct a rational to better discriminate and describe these clusters, identifying specific behaviours related to the global prevalence from March until the end of October or highlight recent evolutions of COVID–19 incidence in the context of a second wave of pandemic. In fact we pinpointed country clusters where COVID–19 reached alarming levels which persist, or have even worsen, at the beginning of the second wave. Additionally, two other clusters were identified: one with countries that seems to be evolving into a situation under control, and another cluster of countries very weakly struck on the first wave, but are now facing a very complex surge, that will test their health systems capacity and timely response regarding covid and non–covid patients. Finally, the worst and more dramatic situation occurred in countries where the number of deaths per 100 000 inhabitants attained an impressive cumulative score.

Introduction: Our paper concern two fundamental pillars to face obesity in adolescence- nutrition education and the phenomenon of human variability, namely in the biological and behavior dimension. Objectives: Assessment of the impact of an innovate school-based nutrition education program (OBESIDATA); the multivariate study of the anthropometric profile and physical activity pattern of adolescents in Portugal; comparison between energy consumption and their energy needs; Evaluation of the accuracy of four commonly used basal metabolic rate prediction equations. Results: After a two weeks period of open interactive digital platform, 85.8% of students increased their nutritional knowledge; the overall prevalence of overweight and obesity in adolescents was 16.5% and 5.9%, respectively; just 38% of participants reported a level of physical activity in line with WHO recommendations; the RMR mean differences of six identified anthropometrics clusters vary from 1349 Kcalories to 1955 Kcalories; the mean reported energy intake was lower than the estimated energy requirements; from all predictive equations estimating energy requirements the relative accuracy, using indirect calorimetric evaluations, is just about 17%. Conclusions: School-based nutrition using technology may provide a practical, attractive and cost- effective strategy to improve nutrition knowledge and eating behaviors; the adolescent’s prevalence of overweight/obesity remains relatively high and physical activity was clear below the WHO recommendations; at average level adolescents REI seems to be lower than their EER, but REI reveals a great individual variability; the accuracy of RMR using predictive equations may have limited applicability; a new paradigma to prevent obesity is coming where genetic will have soon a practical central role.1,2

Introduction: Adolescence is one of the most complex transitions in the life span. It is characterized by changes in body composition, dietary intake, physical activity and sedentary behavior. Anthropometry is of special importance during this period as it allows the monitoring and assessment of the changes in growth and maturation. Additionally, adolescent anthropometry provides indicators of nutritional status and health risk, being a crucial tool to diagnose obesity and to the evolution of caloric needs. Objective: The objective of the present study was to describe Portuguese adolescents’ anthropometric profile, Resting Metabolic Rate (RMR) and physical activity (PA) level. Methods: The sample included 946 adolescents from 6 Portuguese schools aged 15-23 years. Weight, height and waist circumference were measured. Body Mass Index (BMI), waist-to-height ratio (WHTR) and Resting Metabolic Rate were calculated. Physical activity level was self-reported. Results: In the present study 6 classes were developed to obtain a typology of the adolescents that would describe their anthropometric profile. Boys were significantly taller, heavier and had a significantly higher RMR than girls (p<0.01). The overall prevalence of overweight/obesity was 16.5% and 5.9%, respectively. Only 38.3% of the participants were engaging in “moderate”, “intense” or “very intense” physical activity and boys were more likely than girls (50.1% versus 29.2%) to engage in these types of physical activity. No significant global association between age and physical activity was found. Conclusion: These results are of concern due to obesity and physical inactivity health consequences, alongside with the high probability of both, obesity and physical inactivity to track into adulthood. Therefore, effective and evidence-based public health interventions to increase physical activity and prevent obesity during adolescence are needed.